Model Comparison 2026

DeepSeek R1 (0528) vs Kimi K2.7 Code

DeepSeek R1 (0528)
DeepSeek · Balanced · Open weights
$0.99/1M · 164K ctx
Kimi K2.7 Code
Moonshot AI · Balanced · Open weights
$1.35/1M · 262K ctx

Community Vote

Pick a winner in each dimension — change your vote anytime.

Output Quality
Correctness and depth of what it produces
Agentic Ability
Tool calls, instruction-following, and multi-step tasks
Speed
Tokens per second and time-to-first-token
Value for $
How much capability you get per dollar
Reliability
Consistent results — fewer refusals, loops, and format breaks

Specs & Pricing, Side by Side

Spec
DeepSeek R1
Kimi K2.7 Code
Maker
DeepSeek
Moonshot AI
Blended price / 1M
$0.99
$1.35
Input / output
$0.50 in · $2.15 out / 1M tokens
$0.61 in · $3.07 out / 1M tokens
Context window
164K
262K
Open weights
Yes
Yes
Tool use
Yes
Yes
Reasoning
Yes
Yes
Output Quality
7.5
8.6
Agentic Ability
7.0
9.2
Speed
6.8
7.8
Value for $
8.6
9.2
Reliability
8.6
8.9

Pricing and capabilities synced from the OpenRouter catalogue. Scores are editorial (0–10).

Verdict: DeepSeek R1 or Kimi K2.7 Code?

Updated 2026-06-22

Choose DeepSeek R1 (0528) if you want reasoning-heavy planning where cost matters. Choose Kimi K2.7 Code if you want cheap, capable open-weight coding agents.

In our editorial scoring, Kimi K2.7 Code leads in 5 of five dimensions (output quality, agentic ability, speed, value for $ and reliability), while DeepSeek R1 (0528) leads in 0. On price, DeepSeek R1 (0528) runs about $0.99 per 1M tokens (blended) and is open-weight; Kimi K2.7 Code is about $1.35 and open-weight.

Where DeepSeek R1 falls short
  • Slow due to long reasoning
  • Weaker at fast tool loops
Full DeepSeek R1 breakdown →
Where Kimi K2.7 Code falls short
  • Below the very top models on hard reasoning
  • Throughput varies by host
Full Kimi K2.7 Code breakdown →

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